Stochastic Linear Programming pp 1-10 | Cite as

# Prerequisites

## Abstract

Linear Programs are special mathematical programming problems. We understand by a *mathematical programming problem* in the Euclidean space ℝ^{ n } the optimization of a given real-valued function — *the objective function* — on a given subset of ℝ^{ n }, the so-called *feasible set*. A mathematical programming problem is called a *linear program* if its objective function is a linear functional on ℝ^{ n } and if the feasible set can be described as the intersection of finitely many halfspaces and at most finitely many hyperplanes in ℝ^{ n }. Hence the feasible set of a linear program may be represented as the solution set of a system of finitely many linear inequalities and, at most, finitely many linear equalities — the so-called (linear) *constraints* — in a finite number of variables.

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